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Record W4405439954 · doi:10.1109/tap.2024.3514092

New and Emerging Directions in the Fields of Antennas and Propagation

2024· article· en· W4405439954 on OpenAlexaff
Christian Pichot, Gregory H. Huff, Yang Yang, Zhihao Jiang, Xuanfeng Tong, Tian Hong Loh, Ala Alemaryeen, Mahmoud Wagih, Sima Noghanian, R Paryani, Yi Huang, Kunio Sakakibara, Francesca Vipiana, Elise Fear, Saikat Chandra Bakshi, R.B. Waterhouse, Julio Urbina, Sascha D. Meinrath, Bono Po-Jen Shih, Rohit Sharma, Vignesh Manohar, Fikadu T. Dagefu, Koichi Ito

Bibliographic record

VenueIEEE Transactions on Antennas and Propagation · 2024
Typearticle
Languageen
FieldEngineering
TopicAntenna Design and Analysis
Canadian institutionsUniversity of Calgary
Fundersnot available
KeywordsDirectional antennaFresnel zone antennaComputer scienceSlot antennaPhysicsAntenna (radio)Telecommunications

Abstract

fetched live from OpenAlex

In this invited paper, the New Technology Directions Committee (NTDC) of the IEEE Antennas and Propagation Society (AP-S) presents new and emerging research directions to commemorate the 70th anniversary of the IEEE Transactions on Antennas and Propagation. The NTDC consists of three working groups (WGs); the members and collaborators of these groups provide their perspectives on topics related to WG themes in this article. WG-1 focuses on the advancement of materials and manufacturing processes for future antenna applications. WG-2 focuses on advances in communications, sensing, and imaging. WG-3 focuses on maximizing the societal impact of wireless connectivity. The discussion in this article ranges from additive manufacturing (AM) techniques and system integration to advanced communications and quantum-based sensing technologies. Numerous applications are explored and a perspective on the digital divide is offered.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.014
Threshold uncertainty score0.047

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0010.005
Scholarly communication0.0060.011
Open science0.0020.003
Research integrity0.0050.008
Insufficient payload (model declined to judge)0.0140.005

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.228
Teacher spread0.216 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueIEEE Transactions on Antennas and PropagationSame topicAntenna Design and AnalysisFrench-language works237,207